{"id":"https://openalex.org/W4409076538","doi":"https://doi.org/10.1109/jiot.2025.3553879","title":"GMS-YOLO: A Lightweight Real-Time Object Detection Algorithm for Pedestrians and Vehicles Under Foggy Conditions","display_name":"GMS-YOLO: A Lightweight Real-Time Object Detection Algorithm for Pedestrians and Vehicles Under Foggy Conditions","publication_year":2025,"publication_date":"2025-04-01","ids":{"openalex":"https://openalex.org/W4409076538","doi":"https://doi.org/10.1109/jiot.2025.3553879"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3553879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3553879","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079231598","display_name":"Yafei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yafei Chen","raw_affiliation_strings":["School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0004-0187-1948","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001918537","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0002-7847-3807"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7847-3807","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011686858","display_name":"Zheng Zou","orcid":"https://orcid.org/0000-0003-1602-531X"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zou","raw_affiliation_strings":["School of Mechanical Engineering, Chongqing University of Technology, Chongqing, China","Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1602-531X","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5116875175","display_name":"Wenxiu Dan","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxiu Dan","raw_affiliation_strings":["School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-0257-7901","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]},{"raw_affiliation_string":"Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I50632499"],"apc_list":null,"apc_paid":null,"fwci":9.0011,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.98459152,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":"13","first_page":"23879","last_page":"23890"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8024225234985352},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6240460872650146},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4674893915653229},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45168668031692505},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.44686171412467957},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4196981191635132},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3571319282054901},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30363625288009644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1303640902042389}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8024225234985352},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6240460872650146},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4674893915653229},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45168668031692505},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.44686171412467957},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4196981191635132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3571319282054901},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30363625288009644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1303640902042389}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3553879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3553879","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G2122523784","display_name":null,"funder_award_id":"CSTB2023NSCQ-LZX0068","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2504335775","https://openalex.org/W2570343428","https://openalex.org/W2748021867","https://openalex.org/W2910159494","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963152299","https://openalex.org/W2963928582","https://openalex.org/W2990763144","https://openalex.org/W3018757597","https://openalex.org/W3035414587","https://openalex.org/W3096609285","https://openalex.org/W3122173535","https://openalex.org/W4200004942","https://openalex.org/W4214588794","https://openalex.org/W4223950281","https://openalex.org/W4226042837","https://openalex.org/W4283066310","https://openalex.org/W4294664184","https://openalex.org/W4297676427","https://openalex.org/W4312961318","https://openalex.org/W4313160863","https://openalex.org/W4318049991","https://openalex.org/W4319300947","https://openalex.org/W4322741918","https://openalex.org/W4323317091","https://openalex.org/W4379386160","https://openalex.org/W4386071764","https://openalex.org/W4386076079","https://openalex.org/W4386076325","https://openalex.org/W4386879370","https://openalex.org/W4387011219","https://openalex.org/W4387885920","https://openalex.org/W4387967419","https://openalex.org/W4388469725","https://openalex.org/W4389890947","https://openalex.org/W4391155126","https://openalex.org/W4400314297","https://openalex.org/W4400381853","https://openalex.org/W4400976933","https://openalex.org/W4401070258","https://openalex.org/W4401441663","https://openalex.org/W4401567518","https://openalex.org/W4402754006","https://openalex.org/W4403770406","https://openalex.org/W4405679827","https://openalex.org/W6750227808","https://openalex.org/W6853538470","https://openalex.org/W6860762246","https://openalex.org/W6868582632"],"related_works":["https://openalex.org/W2737719445","https://openalex.org/W2898210368","https://openalex.org/W4239098401","https://openalex.org/W2382480268","https://openalex.org/W1976518449","https://openalex.org/W2732837990","https://openalex.org/W2755342338","https://openalex.org/W2363366881","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"In":[0],"conditions":[1],"of":[2,53,100,103,125,143,180,208,244],"foggy":[3,249],"weather,":[4],"challenges,":[5,32],"such":[6],"as":[7,71,89],"low":[8,235],"light,":[9],"blurred":[10],"imagery,":[11],"and":[12,41,56,131,145,154,168,189,210,215,242],"dense":[13],"fog":[14],"that":[15,195],"obscures":[16],"target":[17],"objects":[18],"are":[19,24],"prevalent.":[20],"Moreover,":[21],"computing":[22],"resources":[23],"limited":[25],"on":[26,46,164,183],"edge":[27],"devices.":[28],"To":[29],"tackle":[30],"these":[31],"a":[33,112,138,202,233],"novel":[34,62],"real-time":[35],"detection":[36,59,149,228,246],"algorithm":[37,136,182,223,256],"GMS-YOLO":[38,135,196,222],"for":[39,212,254],"pedestrians":[40],"vehicles":[42],"is":[43,68,87,119,172,257],"proposed":[44,221],"based":[45],"YOLOv10,":[47],"which":[48,94],"overcomes":[49],"the":[50,54,72,90,98,101,104,108,123,126,148,152,162,169,178,181,184,198,213,220,240],"semantic":[51],"bottleneck":[52],"model":[55,163,236],"enhances":[57],"its":[58],"performance.":[60],"A":[61],"ghost":[63,73],"multiscale":[64],"convolution":[65],"(GMSConv)":[66],"module":[67],"constructed,":[69],"serving":[70],"multiScale":[74],"feature":[75],"extraction":[76],"backbone":[77],"network":[78],"(GMS-Net).":[79],"The":[80,134,251],"Shape":[81],"Consistent":[82],"Intersection":[83],"over":[84],"Union":[85],"(SCIoU)":[86],"introduced":[88],"localization":[91],"loss":[92,109],"function,":[93],"takes":[95],"into":[96],"account":[97],"influence":[99],"attributes":[102],"regression":[105,132],"box":[106],"in":[107,248],"computation.":[110],"Additionally,":[111],"compensatory":[113],"consistency":[114],"matching":[115],"metric":[116,128],"(CCMM)":[117],"formula":[118],"designed":[120],"to":[121,129],"reduce":[122],"sensitivity":[124],"original":[127],"IoU":[130],"scores.":[133],"has":[137],"lightweight":[139],"structure,":[140],"achieving":[141],"FPS":[142],"94":[144],"92":[146],"during":[147],"phase":[150],"at":[151],"\u201c\u2018n\u201d\u2019":[153],"\u201c\u2018s\u201d\u2019":[155],"sizes,":[156],"respectively.":[157,218],"Furthermore,":[158],"we":[159],"have":[160],"deployed":[161],"Jetson":[165],"Nano":[166],"hardware,":[167],"inference":[170],"speed":[171],"also":[173,231],"quite":[174],"encouraging.":[175],"We":[176],"validated":[177],"effectiveness":[179],"Foggy":[185],"Cityscapes,":[186],"RTTS,":[187],"VOC2007-fog,":[188],"VOC2012-fog":[190],"datasets.":[191],"Experimental":[192],"results":[193],"indicate":[194],"outperforms":[197],"baseline":[199],"model,":[200],"with":[201],"mean":[203],"average":[204],"precision":[205],"(mAP)":[206],"improvement":[207],"6.3%":[209],"5.5%":[211],"\u201cn\u201d":[214],"\u201cs\u201d":[216],"scales,":[217],"Consequently,":[219],"not":[224],"only":[225],"demonstrates":[226],"superior":[227],"performance":[229],"but":[230],"maintains":[232],"relatively":[234],"complexity,":[237],"significantly":[238],"enhancing":[239],"efficiency":[241],"accuracy":[243],"object":[245],"tasks":[247],"environments.":[250],"source":[252],"code":[253],"our":[255],"available":[258],"at:https://github.com/Fwdchina/GMS-YOLO.":[259]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":7}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
